The feasibility of hand-held thermal and UAV-based multispectral imaging for canopy water status assessment and yield prediction of irrigated African eggplant (Solanum aethopicum L)

This study was conducted to evaluate the feasibility of a mobile phone-based thermal and UAV-based multispectral imaging assess irrigation performance African eggplant. The used randomized block design (RBD) with sub-plots being irrigated at 100% (I100), 80% (I80) 60% (I60) calculated crop water requirements using drip. leaf moisture content monitored different soil conditions early, vegetative full stages. results showed that, stress index (CWSI) derived from images is sensitive (LMC) in I80 I60 all UAV-derived Normalized Difference Vegetation Index (NDVI) Optimized Soil Adjusted (OSAVI) correlated LMC stages for three treatments. In cases where eggplant under normal conditions, use NDVI or OSAVI will be able predict yields. where, grown deficit irrigation, CWSI can next depending on available resources.